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Using Self-Learning AI to defend against zero-day and N-day attacks

Jul 2022

N-days are often overlooked by security teams yet often attract just as much attention as their zero-day counterpart. This blog explores both a zero-day and n-day attack on two different customer’s SonicWall VPN server and Atlassian Confluence server, respectively, detailing how Darktrace was able to detect and intervene before any irreparable damage occurred.

‍Key Terms:

Zero-day | A recently discovered security vulnerability in computer software that has no currently available fix or patch. Its name come from the reality that vendors have “zero days” to act and respond.

N-day | A vulnerability that emerges in computer software in which a vendor is aware and may have already issued (or are currently working on) a patch or fix. Active exploits often already exist and await abuse by nefarious actors.

Traditional security solutions often apply signature-based-detection when identifying cyber threats, helping to defend against legacy attacks but consequently missing novel ones. Therefore, security teams often lend a lot of focus to ensuring that the risk of zero-day vulnerabilities is reduced [1]. As explored in this blog, however, organizations can face just as much of a risk from n-day attacks, since they invite the most attention from malicious actors [2]. This is due in part to the reduced complexity, cost and time invested in researching and finding new exploits compared with that found when attackers exploit zero-days.

This blog will examine both a zero-day and n-day attack that two different Darktrace customers faced in the fall of 2021. This will include the activity Darktrace detected, along with the steps taken by Darktrace/Network to intervene. It will then compare the incidents, discuss the possible dangers of third-party integrations, and assess the deprecation of legacy security tools.

Revisiting zero-day attacks

Zero-days are among the greatest concerns security teams face in the era of modern technology and networking. Defending critical systems from zero-day compromises is a task most legacy security solutions are often unable to handle. Due to the complexity of uncovering new security flaws and developing elaborate code that can exploit them, these attacks are often carried out by funded or experienced groups such as nation-state actors and APTs. One of history’s most prolific zero-days, ‘Stuxnet’, sent security teams worldwide into a global panic in 2010. This involved a widespread attack on Iranian nuclear infrastructure and was widely accepted to be a result of nation-state actors [3]. The Stuxnet worm took advantage of four zero-day exploits, compromising over 200,000 devices and physically damaging around 10% of the 9,000 critical centrifuges at the Natanz nuclear site.

More recently, 2021 saw the emergence of several critical zero-day vulnerabilities within SonicWall’s product suite [4]. SonicWall is a security hardware manufacturer that provides hardware firewall devices, unified threat management, VPN gateways and network security solutions. Some of these vulnerabilities lie within their Secure Mobile Access (SMA) 100 series (for example, CVE-2019-7481, CVE-2021-20016 and CVE-2021-20038 to name a few). These directly affected VPN devices and often allowed attackers easy remote access to company devices. CVE-2021-20016 in particular incorporates an SQL-Injection vulnerability within SonicWall’s SSL VPN SMA 100 product line [5]. If exploited, this defect would allow an unauthenticated remote attacker to perform their own malicious SQL query in order to access usernames, passwords and other session related information.

The N-day underdog

The shadow cast by zero-day attacks often shrouds that of n-day attacks. N-days, however, often pose an equal - if not greater - risk to the majority of organizations, particularly those in industrial sectors. Since these vulnerabilities have fixes available, all of the hard work around research is already done; malicious actors only need to view proof of concepts (POCs) or, if proficient in coding, reverse-engineer software to reveal code-changes (binary diffing) in order to exploit these security flaws in the wild. These vulnerabilities are typically attributed to opportunistic hackers and script-kiddies, where little research or heavy lifting is required.

August 2021 gave rise to a critical vulnerability in Atlassian Confluence servers, namely CVE-2021-26084 [6]. Confluence is a widely used collaboration wiki tool and knowledge-sharing platform. As introduced and discussed a few months ago in a previous Darktrace blog, this vulnerability allows attackers to remotely execute code on internet-facing servers after exploiting injection vulnerabilities in Object-Graph Navigation Language (OGNL). Whilst Confluence had patches and fixes available to users, attackers still jumped on this opportunity and began scanning the internet for signs of critical devices serving this outdated software [7]. Once identified, they would exploit the vulnerability, often installing crypto mining software onto the device. More recently, Darktrace explored a new vulnerability (CVE-2022-26134), disclosed midway through 2022, that affected Confluence servers and data centers using similar techniques to that found in CVE-2021-26084 [8].

SonicWall in the wild – 1. Zero-day attack

At the beginning of August 2021, Darktrace prevented an attack from taking place within a European automotive customer’s environment (Figure 1). The attack targeted a vulnerable internet-facing SonicWall VPN server, and while the attacker’s motive remains unclear, similar historic events suggest that they intended to perform ransomware encryption or data exfiltration.

Figure 1: Timeline of the SonicWall attack

Darktrace was unable to confirm the definite tactics, techniques and procedures (TTPs) used by the attacker to compromise the customer’s environment, as the device was compromised before Darktrace installation and coverage. However, from looking at recently disclosed SonicWall VPN vulnerabilities and patterns of behaviour, it is likely CVE-2021-20016 played a part. At some point after this initial infection, it is also believed the device was able to move laterally to a domain controller (DC) using administrative credentials; it was this server that then initiated the anomalous activity that Darktrace detected and alerted on.

On August 5^th 2021 , Darktrace observed this compromised domain controller engaging in unusual ICMP scanning - a protocol used to discover active devices within an environment and create a map of an organization’s network topology. Shortly after, the infected server began scanning devices for open RDP ports and enumerating SMB shares using unorthodox methods. SMB delete and HTTP requests (over port 445 and 80 respectively) were made for files named delete.me in the root directory of numerous network shares using the user agent Microsoft WebDAV. However, no such files appeared to exist within the environment. This may have been the result of an attacker probing devices in the network in an effort to see their responses and gather information on properties and vulnerabilities they could later exploit.

Soon the infected DC began establishing RDP tunnels back to the VPN server and making requests to an internal DNS server for multiple endpoints relating to exploit kits, likely in an effort to strengthen the attacker’s foothold within the environment. Some of the endpoints requested relate to:

- EternalBlue vulnerability

- Petit Potam NTLM hash attack tool

- Unusual GitHub repositories

- Unusual Python repositories

The DC made outgoing NTLM requests to other internal devices, implying the successful installation of Petit Potam exploitation tools. The server then began performing NTLM reconnaissance, making over 1,000 successful logins under ‘Administrator’ to several other internal devices. Around the same time, the device was also seen making anonymous SMBv1 logins to numerous internal devices, (possibly symptomatic of the attacker probing machines for EternalBlue vulnerabilities).

Interestingly, the device also made numerous failed authentication attempts using a spoofed credential for one of the organization’s security managers. This was likely in an attempt to hide themselves using ‘Living off the Land’ (LotL) techniques. However, whilst the attacker clearly did their research on the company, they failed to acknowledge the typical naming convention used for credentials within the environment. This ultimately backfired and made the compromise more obvious and unusual.

In the morning of the following day, the initially compromised VPN server began conducting further reconnaissance, engaging in similar activity to that observed by the domain controller. Until now, the customer had set Darktrace RESPOND to run in human confirmation mode, meaning interventions were not made autonomously but required confirmation by a member of the internal security team. However, thanks to Proactive Threat Notifications (PTNs) delivered by Darktrace’s dedicated SOC team, the customer was made immediately aware of this unusual behaviour, allowing them to apply manual Darktrace RESPOND blocks to all outgoing connections (Figure 2). This gave the security team enough time to respond and remediate before serious damage could be done.

Figure 2: Darktrace RESPOND model breach showing the manually applied “Quarantine Device” action taken against the compromised VPN server. This screenshot displays the UI from Darktrace version 5.1

Confluence in the wild – 2. N-day attack

Towards the end of 2021, Darktrace saw a European broadcasting customer leave an Atlassian Confluence internet-facing server unpatched and vulnerable to crypto-mining malware using CVE-2021-26084. Thanks to Darktrace, this attack was entirely immobilized within only a few hours of the initial infection, protecting the organization from damage (Figure 3).

Figure 3: Timeline of the Confluence attack

On midday on September 1^st 2021, an unpatched Confluence server was seen receiving SSL connections over port 443 from a suspicious new endpoint, 178.238.226[.]127. The connections were encrypted, meaning Darktrace was unable to view the contents and ascertain what requests were being made. However, with the disclosure of CVE-2021-26084 just 7 days prior to this activity, it is likely that the TTPs used involved injecting OGNL expressions to Confluence server memory; allowing the attacker to remotely execute code on the vulnerable server.

Immediately after successful exploitation of the Confluence server, the infected device was observed making outgoing HTTP GET requests to several external endpoints using a new user agent (curl/7.61.1). Curl was used to silently download and configure multiple suspicious files relating to XMRig cryptocurrency miner, including ld.sh, XMRig and config.json. Subsequent outgoing connections were then made to europe.randomx-hub.miningpoolhub[.]com · 172.105.210[.]117 using the JSON-RPC protocol, seen alongside the mining credential maillocal.confluence (Figure 4). Only 3 seconds after initial compromise, the infected device began attempting to mine cryptocurrency using the Minergate protocol but was instantly and autonomously blocked by Darktrace RESPOND. This prevented the server from abusing system resources and generating profits for the attacker.

Figure 4: A graph showing the frequency of external connections using the JSON-RPC protocol made by the breach device over a 48-hour window. The orange-red dots represent models that breached as a result of this activity, demonstrating the “waterfall” effect commonly seen when a device suffers a compromise. This screenshot displays the UI from Darktrace version 5.1

In the afternoon, the malware persisted with its infection. The compromised server began making successive HTTP GET requests to a new rare endpoint 195.19.192[.]28 using the same curl user agent (Figures 5 & 6). These requests were for executable and dynamic library files associated with Kinsing malware (but fortunately were also blocked by Darktrace RESPOND). Kinsing is a malware strain found in numerous attack campaigns which is often associated with crypto-jacking, and has appeared in previous Darktrace blogs [9].

Figure 5: Cyber AI Analyst summarising the unusual download of Kinsing software using the new curl user agent. This screenshot displays the UI from Darktrace version 5.1

The attacker then began making HTTP POST requests to an IP 185.154.53[.]140, using the same curl user agent; likely a method for the attacker to maintain persistence within the network and establish a foothold using its C2 infrastructure. The Confluence server was then again seen attempting to mine cryptocurrency using the Minergate protocol. It made outgoing JSON-RPC connections to a different new endpoint, 45.129.2[.]107, using the following mining credential: ‘42J8CF9sQoP9pMbvtcLgTxdA2KN4ZMUVWJk6HJDWzixDLmU2Ar47PUNS5XHv4Kmfdh8aA9fbZmKHwfmFo8Wup8YtS5Kdqh2’. This was once again blocked by Darktrace RESPOND (Figure 7).

Figure 6: VirusTotal showing the unusualness of one of these external IPs [10]

Figure 7: Log data showing the action taken by Darktrace RESPOND in response to the device breaching the “Crypto Currency Mining Activity” model. This screenshot displays the UI from Darktrace version 5.1

The final activity seen from this device involved the download of additional shell scripts over HTTP associated with Kinsing, namely spre.sh and unk.sh, from 194.38.20[.]199 and 195.3.146[.]118 respectively (Figure 8). A new user agent (Wget/1.19.5 (linux-gnu)) was used when connecting to the latter endpoint, which also began concurrently initiating repeated connections indicative of C2 beaconing. These scripts help to spread the Kinsing malware laterally within the environment and may have been the attacker's last ditch efforts at furthering their compromise before Darktrace RESPOND blocked all connections from the infected Confluence server [11]. With Darktrace RESPOND's successful actions, the customer’s security team were then able to perform their own response and remediation.

Figure 8: Cyber AI Analyst revealing the last ditch efforts made by the threat actor to download further malicious software. This screenshot displays the UI from Darktrace version 5.1

Darktrace Coverage: N- vs Zero-days

In the SonicWall case the attacker was unable to achieve their actions on objectives (thanks to Darktrace's intervention). However, this incident displayed tactics of a more stealthy and sophisticated attacker - they had an exploited machine but waited for the right moment to execute their malicious code and initiate a full compromise. Due to the lack of visibility over attacker motive, it is difficult to deduce what type of actor led to this intrusion. However, with the disclosure of a zero-day vulnerability (CVE-2021-20016) not long before this attack, along with a seemingly dormant initially compromised device, it is highly possible that it was carried out by a sophisticated cyber criminal or gang.

On the other hand, the Confluence case engaged in a slightly more noisy approach; it dropped crypto mining malware on vulnerable devices in the hope that the target’s security team did not maintain visibility over their network or would merely turn a blind eye. The files downloaded and credentials observed alongside the mining activity heavily imply the use of Kinsing malware [11]. Since this vulnerability (CVE-2021-26084) emerged as an n-day attack with likely easily accessible POCs, as well as there being a lack of LotL techniques and the motive being long term monetary gain, it is possible this attack was conducted by a less sophisticated or amateur actor (script-kiddie); one that opportunistically exploits known vulnerabilities in internet-facing devices in order to make a quick profit [12].

Whilst Darktrace RESPOND was enabled in human confirmation mode only during the start of the SonicWall attack, Darktrace’s Cyber AI Analyst still offered invaluable insight into the unusual activity associated with the infected machines during both the Confluence and SonicWall compromises. SOC analysts were able to see these uncharacteristic behaviours and escalate the incident through Darktrace’s PTN and ATE services. Analysts then worked through these tickets with the customers, providing support and guidance and, in the SonicWall case, quickly helping to configure Darktrace RESPOND. In both scenarios, Darktrace RESPOND was able to block abnormal connections and enforce a device’s pattern of life, affording the security team enough time to isolate the infected machines and prevent further threats such as ransomware detonation or data exfiltration.

Concluding thoughts and dangers of third-party integrations

Organizations with internet-facing devices will inevitably suffer opportunistic zero-day and n-day attacks. While little can be done to remove the risk of zero-days entirely, ensuring that organizations keep their systems up to date will at the very least help prevent opportunistic and script-kiddies from exploiting n-day vulnerabilities.

However, it is often not always possible for organizations to keep their systems up to date, especially for those who require continuous availability. This may also pose issues for organizations that rely on, and put their trust in, third party integrations such as those explored in this blog (Confluence and SonicWall), as enforcing secure software is almost entirely out of their hands. Moreover, with the rising prevalence of remote working, it is essential now more than ever that organizations ensure their VPN devices are shielded from external threats, guidance on which has been released by the NSA/CISA [13].

These two case studies have shown that whilst organizations can configure their networks and firewalls to help identify known indicators of compromise (IoC), this ‘rearview mirror’ approach will not account for, or protect against, any new and undisclosed IoCs. With the aid of Self-Learning AI and anomaly detection, Darktrace can detect the slightest deviation from a device’s normal pattern of life and respond autonomously without the need for rules and signatures. This allows for the disruption and prevention of known and novel attacks before irreparable damage is caused- reassuring security teams that their digital estates are secure.

Thanks to Paul Jennings for his contributions to this blog.

Appendices: SonicWall (Zero-day)

Darktrace model detections

· AIA / Suspicious Chain of Administrative Credentials

· Anomalous Connection / Active Remote Desktop Tunnel

· Anomalous Connection / SMB Enumeration

· Anomalous Connection / Unusual Internal Remote Desktop

· Compliance / High Priority Compliance Model Breach

· Compliance / Outgoing NTLM Request from DC

· Device / Anomalous RDP Followed By Multiple Model Breaches

· Device / Anomalous SMB Followed By Multiple Model Breaches

· Device / ICMP Address Scan

· Device / Large Number of Model Breaches

· Device / Large Number of Model Breaches from Critical Network Device

· Device / Multiple Lateral Movement Model Breaches (PTN/Enhanced Monitoring model)

· Device / Network Scan

· Device / Possible SMB/NTLM Reconnaissance

· Device / RDP Scan

· Device / Reverse DNS Sweep

· Device / SMB Session Bruteforce

· Device / Suspicious Network Scan Activity (PTN/Enhanced Monitoring model)

· Unusual Activity / Possible RPC Recon Activity

Darktrace RESPOND (Antigena) actions (as displayed in example)

· Antigena / Network / Manual / Quarantine Device

MITRE ATT&CK Techniques Observed

IoCs

‍

Appendices: Confluence (N-day)

Darktrace model detections

· Anomalous Connection / New User Agent to IP Without Hostname

· Anomalous Connection / Posting HTTP to IP Without Hostname

· Anomalous File / EXE from Rare External Location

· Anomalous File / Script from Rare Location

· Compliance / Crypto Currency Mining Activity

· Compromise / High Priority Crypto Currency Mining (PTN/Enhanced Monitoring model)

· Device / Initial Breach Chain Compromise (PTN/Enhanced Monitoring model)

· Device / Internet Facing Device with High Priority Alert

· Device / New User Agent

Darktrace RESPOND (Antigena) actions (displayed in example)

· Antigena / Network / Compliance / Antigena Crypto Currency Mining Block

· Antigena / Network / External Threat / Antigena File then New Outbound Block

· Antigena / Network / External Threat / Antigena Suspicious Activity Block

· Antigena / Network / External Threat / Antigena Suspicious File Block

· Antigena / Network / Significant Anomaly / Antigena Block Enhanced Monitoring

MITRE ATT&CK Techniques Observed

IOCs

References:

[1] https://securitybrief.asia/story/why-preventing-zero-day-attacks-is-crucial-for-businesses

[2] https://electricenergyonline.com/energy/magazine/1150/article/Security-Sessions-More-Dangerous-Than-Zero-Days-The-N-Day-Threat.htm

[3] https://www.wired.com/2014/11/countdown-to-zero-day-stuxnet/

[4] https://cve.mitre.org/cgi-bin/cvekey.cgi?keyword=SonicWall+2021

[5] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-20016

[6] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-26084

[7] https://www.zdnet.com/article/us-cybercom-says-mass-exploitation-of-atlassian-confluence-vulnerability-ongoing-and-expected-to-accelerate/

[8] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-26134

[9] https://attack.mitre.org/software/S0599/

[10] https://www.virustotal.com/gui/ip-address/195.19.192.28/detection

[11] https://sysdig.com/blog/zoom-into-kinsing-kdevtmpfsi/

[12] https://github.com/alt3kx/CVE-2021-26084_PoC

[13] https://www.nsa.gov/Press-Room/Press-Releases-Statements/Press-Release-View/Article/2791320/nsa-cisa-release-guidance-on-selecting-and-hardening-remote-access-vpns/

INSIDE THE SOC

Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.

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ABOUT ThE AUTHOR

Lewis Morgan

Cyber Analyst

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Inside the SOC

Sliver C2: How Darktrace Provided a Sliver of Hope in the Face of an Emerging C2 Framework

Apr 2024

Offensive Security Tools

As organizations globally seek to for ways to bolster their digital defenses and safeguard their networks against ever-changing cyber threats, security teams are increasingly adopting offensive security tools to simulate cyber-attacks and assess the security posture of their networks. These legitimate tools, however, can sometimes be exploited by real threat actors and used as genuine actor vectors.

What is Sliver C2?

Sliver C2 is a legitimate open-source command-and-control (C2) framework that was released in 2020 by the security organization Bishop Fox. Silver C2 was originally intended for security teams and penetration testers to perform security tests on their digital environments [1] [2] [5]. In recent years, however, the Sliver C2 framework has become a popular alternative to Cobalt Strike and Metasploit for many attackers and Advanced Persistence Threat (APT) groups who adopt this C2 framework for unsolicited and ill-intentioned activities.

The use of Sliver C2 has been observed in conjunction with various strains of Rust-based malware, such as KrustyLoader, to provide backdoors enabling lines of communication between attackers and their malicious C2 severs [6]. It is unsurprising, then, that it has also been leveraged to exploit zero-day vulnerabilities, including critical vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

In early 2024, Darktrace observed the malicious use of Sliver C2 during an investigation into post-exploitation activity on customer networks affected by the Ivanti vulnerabilities. Fortunately for affected customers, Darktrace DETECT™ was able to recognize the suspicious network-based connectivity that emerged alongside Sliver C2 usage and promptly brought it to the attention of customer security teams for remediation.

How does Silver C2 work?

Given its open-source nature, the Sliver C2 framework is extremely easy to access and download and is designed to support multiple operating systems (OS), including MacOS, Windows, and Linux [4].

Sliver C2 generates implants (aptly referred to as ‘slivers’) that operate on a client-server architecture [1]. An implant contains malicious code used to remotely control a targeted device [5]. Once a ‘sliver’ is deployed on a compromised device, a line of communication is established between the target device and the central C2 server. These connections can then be managed over Mutual TLS (mTLS), WireGuard, HTTP(S), or DNS [1] [4]. Sliver C2 has a wide-range of features, which include dynamic code generation, compile-time obfuscation, multiplayer-mode, staged and stageless payloads, procedurally generated C2 over HTTP(S) and DNS canary blue team detection [4].

Why Do Attackers Use Sliver C2?

Amidst the multitude of reasons why malicious actors opt for Sliver C2 over its counterparts, one stands out: its relative obscurity. This lack of widespread recognition means that security teams may overlook the threat, failing to actively search for it within their networks [3] [5].

Although the presence of Sliver C2 activity could be representative of authorized and expected penetration testing behavior, it could also be indicative of a threat actor attempting to communicate with its malicious infrastructure, so it is crucial for organizations and their security teams to identify such activity at the earliest possible stage.

Darktrace’s Coverage of Sliver C2 Activity

Darktrace’s anomaly-based approach to threat detection means that it does not explicitly attempt to attribute or distinguish between specific C2 infrastructures. Despite this, Darktrace was able to connect Sliver C2 usage to phases of an ongoing attack chain related to the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPN appliances in January 2024.

Around the time that the zero-day Ivanti vulnerabilities were disclosed, Darktrace detected an internal server on one customer network deviating from its expected pattern of activity. The device was observed making regular connections to endpoints associated with Pulse Secure Cloud Licensing, indicating it was an Ivanti server. It was observed connecting to a string of anomalous hostnames, including ‘cmjk3d071amc01fu9e10ae5rt9jaatj6b.oast[.]live’ and ‘cmjft14b13vpn5vf9i90xdu6akt5k3pnx.oast[.]pro’, via HTTP using the user agent ‘curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7’.

Darktrace further identified that the URI requested during these connections was ‘/’ and the top-level domains (TLDs) of the endpoints in question were known Out-of-band Application Security Testing (OAST) server provider domains, namely ‘oast[.]live’ and ‘oast[.]pro’. OAST is a testing method that is used to verify the security posture of an application by testing it for vulnerabilities from outside of the network [7]. This activity triggered the DETECT model ‘Compromise / Possible Tunnelling to Bin Services’, which breaches when a device is observed sending DNS requests for, or connecting to, ‘request bin’ services. Malicious actors often abuse such services to tunnel data via DNS or HTTP requests. In this specific incident, only two connections were observed, and the total volume of data transferred was relatively low (2,302 bytes transferred externally). It is likely that the connections to OAST servers represented malicious actors testing whether target devices were vulnerable to the Ivanti exploits.

The device proceeded to make several SSL connections to the IP address 103.13.28[.]40, using the destination port 53, which is typically reserved for DNS requests. Darktrace recognized that this activity was unusual as the offending device had never previously been observed using port 53 for SSL connections.

Figure 1: Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.

Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.

Further investigation into the suspicious IP address revealed that it had been flagged as malicious by multiple open-source intelligence (OSINT) vendors [8]. In addition, OSINT sources also identified that the JARM fingerprint of the service running on this IP and port (00000000000000000043d43d00043de2a97eabb398317329f027c66e4c1b01) was linked to the Sliver C2 framework and the mTLS protocol it is known to use [4] [5].

An Additional Example of Darktrace’s Detection of Sliver C2

However, it was not just during the January 2024 exploitation of Ivanti services that Darktrace observed cases of Sliver C2 usages across its customer base. In March 2023, for example, Darktrace detected devices on multiple customer accounts making beaconing connections to malicious endpoints linked to Sliver C2 infrastructure, including 18.234.7[.]23 [10] [11] [12] [13].

Darktrace identified that the observed connections to this endpoint contained the unusual URI ‘/NIS-[REDACTED]’ which contained 125 characters, including numbers, lower and upper case letters, and special characters like “_”, “/”, and “-“, as well as various other URIs which suggested attempted data exfiltration:

‘/upload/api.html?c=[REDACTED] &fp=[REDACTED]’

‘/samples.html?mx=[REDACTED] &s=[REDACTED]’
‘/actions/samples.html?l=[REDACTED] &tc=[REDACTED]’
‘/api.html?gf=[REDACTED] &x=[REDACTED]’
‘/samples.html?c=[REDACTED] &zo=[REDACTED]’

This anomalous external connectivity was carried out through multiple destination ports, including the key ports 443 and 8888.

Darktrace additionally observed devices on affected customer networks performing TLS beaconing to the IP address 44.202.135[.]229 with the JA3 hash 19e29534fd49dd27d09234e639c4057e. According to OSINT sources, this JA3 hash is associated with the Golang TLS cipher suites in which the Sliver framework is developed [14].

Conclusion

Despite its relative novelty in the threat landscape and its lesser-known status compared to other C2 frameworks, Darktrace has demonstrated its ability effectively detect malicious use of Sliver C2 across numerous customer environments. This included instances where attackers exploited vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

While human security teams may lack awareness of this framework, and traditional rules and signatured-based security tools might not be fully equipped and updated to detect Sliver C2 activity, Darktrace’s Self Learning AI understands its customer networks, users, and devices. As such, Darktrace is adept at identifying subtle deviations in device behavior that could indicate network compromise, including connections to new or unusual external locations, regardless of whether attackers use established or novel C2 frameworks, providing organizations with a sliver of hope in an ever-evolving threat landscape.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant

Appendices

DETECT Model Coverage

Compromise / Repeating Connections Over 4 Days
Anomalous Connection / Application Protocol on Uncommon Port
Anomalous Server Activity / Server Activity on New Non-Standard Port
Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
Compromise / Quick and Regular Windows HTTP Beaconing
Compromise / High Volume of Connections with Beacon Score
Anomalous Connection / Multiple Failed Connections to Rare Endpoint
Compromise / Slow Beaconing Activity To External Rare
Compromise / HTTP Beaconing to Rare Destination
Compromise / Sustained SSL or HTTP Increase
Compromise / Large Number of Suspicious Failed Connections
Compromise / SSL or HTTP Beacon
Compromise / Possible Malware HTTP Comms
Compromise / Possible Tunnelling to Bin Services
Anomalous Connection / Low and Slow Exfiltration to IP
Device / New User Agent
Anomalous Connection / New User Agent to IP Without Hostname
Anomalous File / EXE from Rare External Location
Anomalous File / Numeric File Download
Anomalous Connection / Powershell to Rare External
Anomalous Server Activity / New Internet Facing System

List of Indicators of Compromise (IoCs)

18.234.7[.]23 - Destination IP - Likely C2 Server

103.13.28[.]40 - Destination IP - Likely C2 Server

44.202.135[.]229 - Destination IP - Likely C2 Server

References

[1] https://bishopfox.com/tools/sliver

[2] https://vk9-sec.com/how-to-set-up-use-c2-sliver/

[3] https://www.scmagazine.com/brief/sliver-c2-framework-gaining-traction-among-threat-actors

[4] https://github[.]com/BishopFox/sliver

[5] https://www.cybereason.com/blog/sliver-c2-leveraged-by-many-threat-actors

[6] https://securityaffairs.com/158393/malware/ivanti-connect-secure-vpn-deliver-krustyloader.html

[7] https://www.xenonstack.com/insights/out-of-band-application-security-testing

[8] https://www.virustotal.com/gui/ip-address/103.13.28.40/detection

[9] https://threatfox.abuse.ch/browse.php?search=ioc%3A107.174.78.227

[10] https://threatfox.abuse.ch/ioc/1074576/

[11] https://threatfox.abuse.ch/ioc/1093887/

[12] https://threatfox.abuse.ch/ioc/846889/

[13] https://threatfox.abuse.ch/ioc/1093889/

[14] https://github.com/projectdiscovery/nuclei/issues/3330

About the author

Natalia Sánchez Rocafort

Cyber Security Analyst

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Email

Looking Beyond Secure Email Gateways with the Latest Innovations to Darktrace/Email

Apr 2024

Organizations Should Demand More from their Email Security

In response to a more intricate threat landscape, organizations should view email security as a critical component of their defense-in-depth strategy, rather than defending the inbox alone with a traditional Secure Email Gateway (SEG). Organizations need more than a traditional gateway – that doubles, instead of replaces, the capabilities provided by native security vendor – and require an equally granular degree of analysis across all messaging, including inbound, outbound, and lateral mail, plus Teams messages.

Darktrace/Email is the industry’s most advanced cloud email security, powered by Self-Learning AI. It combines AI techniques to exceed the accuracy and efficiency of leading security solutions, and is the only security built to elevate, not duplicate, native email security.

With its largest update ever, Darktrace/Email introduces the following innovations, finally allowing security teams to look beyond secure email gateways with autonomous AI:

AI-augmented data loss prevention to stop the entire spectrum of outbound mail threats
an easy way to deploy DMARC quickly with AI
major enhancements to streamline SOC workflows and increase the detection of sophisticated phishing links
expansion of Darktrace’s leading AI prevention to lateral mail, account compromise and Microsoft Teams

What’s New with Darktrace/Email

Data Loss Prevention

Block the entire spectrum of outbound mail threats with advanced data loss prevention that builds on tags in native email to stop unknown, accidental, and malicious data loss

Darktrace understands normal at individual user, group and organization level with a proven AI that detects abnormal user behavior and dynamic content changes. Using this understanding, Darktrace/Email actions outbound emails to stop unknown, accidental and malicious data loss.

Traditional DLP solutions only take into account classified data, which relies on the manual input of labelling each data piece, or creating rules to catch pattern matches that try to stop data of certain types leaving the organization. But in today’s world of constantly changing data, regular expression and fingerprinting detection are no longer enough.

Human error – Because it understands normal for every user, Darktrace/Email can recognize cases of misdirected emails. Even if the data is correctly labelled or insensitive, Darktrace recognizes when the context in which it is being sent could be a case of data loss and warns the user.
Unclassified data – Whereas traditional DLP solutions can only take action on classified data, Darktrace analyzes the range of data that is either pending labels or can’t be labeled with typical capabilities due to its understanding of the content and context of every email.
Insider threat – If a malicious actor has compromised an account, data exfiltration may still be attempted on encrypted, intellectual property, or other forms of unlabelled data to avoid detection. Darktrace analyses user behaviour to catch cases of unusual data exfiltration from individual accounts.

And classification efforts already in place aren’t wasted – Darktrace/Email extends Microsoft Purview policies and sensitivity labels to avoid duplicate workflows for the security team, combining the best of both approaches to ensure organizations maintain control and visibility over their data.

End User and Security Workflows

Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks¹

Darktrace/Email improves end-user reporting from the ground up to save security team resource. Employees will always be on the front line of email security – while other solutions assume that end-user reporting is automatically of poor quality, Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one.

Users are empowered to assess and report suspicious activity with contextual banners and Cyber AI Analyst generated narratives for potentially suspicious emails, resulting in 60% fewer benign emails reported.

Out of the higher-quality emails that end up being reported, the next step is to reduce the amount of emails that reach the SOC. Darktrace/Email’s Mailbox Security Assistant automates their triage with secondary analysis combining additional behavioral signals – using x20 more metrics than previously – with advanced link analysis to detect 70% more sophisticated malicious phishing links.² This directly alleviates the burden of manual triage for security analysts.

For the emails that are received by the SOC, Darktrace/Email uses automation to reduce time spent investigating per incident. With live inbox view, security teams gain access to a centralized platform that combines intuitive search capabilities, Cyber AI Analyst reports, and mobile application access. Analysts can take remediation actions from within Darktrace/Email, eliminating console hopping and accelerating incident response.

Darktrace takes a user-focused and business-centric approach to email security, in contrast to the attack-centric rules and signatures approach of secure email gateways

Microsoft Teams

Detect threats within your Teams environment such as account compromise, phishing, malware and data loss

Around 83% of Fortune 500 companies rely on Microsoft Office products and services, particularly Teams and SharePoint.³

Darktrace now leverages the same behavioral AI techniques for Microsoft customers across 365 and Teams, allowing organizations to detect threats and signals of account compromise within their Teams environment including social engineering, malware and data loss.

The primary use case for Microsoft Teams protection is as a potential entry vector. While messaging has traditionally been internal only, as organizations open up it is becoming an entry vector which needs to be treated with the same level of caution as email. That’s why we’re bringing our proven AI approach to Microsoft Teams, that understands the user behind the message.

Anomalous messaging behavior is also a highly relevant indicator of whether a user has been compromised. Unlike other solutions that analyze Microsoft Teams content which focus on payloads, Darktrace goes beyond basic link and sandbox analysis and looks at actual user behavior from both a content and context perspective. This linguistic understanding isn’t bound by the requirement to match a signature to a malicious payload, rather it looks at the context in which the message has been delivered. From this analysis, Darktrace can spot the early symptoms of account compromise such as early-stage social engineering before a payload is delivered.

Lateral Mail Analysis

Detect and respond to internal mailflow with multi-layered AI to prevent account takeover, lateral phishing and data leaks

The industry’s most robust account takeover protection now prevents lateral mail account compromise. Darktrace has always looked at internal mail to inform inbound and outbound decisions, but will now elevate suspicious lateral mail behaviour using the same AI techniques for inbound, outbound and Teams analysis.

Darktrace integrates signals from across the entire mailflow and communication patterns to determine symptoms of account compromise, now including lateral mailflow

Unlike other solutions which only analyze payloads, Darktrace analyzes a whole range of signals to catch lateral movement before a payload is delivered. Contributing yet another layer to the AI behavioral profile for each user, security teams can now use signals from lateral mail to spot the early symptoms of account takeover and take autonomous actions to prevent further compromise.

DMARC

Gain in-depth visibility and control of 3rd parties using your domain with an industry-first AI-assisted DMARC

Darktrace has created the easiest path to brand protection and compliance with the new Darktrace/DMARC. This new capability continuously stops spoofing and phishing from the enterprise domain, while automatically enhancing email security and reducing the attack surface.

Darktrace/DMARC helps to upskill businesses by providing step by step guidance and automated record suggestions provide a clear, efficient road to enforcement. It allows organizations to quickly achieve compliance with requirements from Google, Yahoo, and others, to ensure that their emails are reaching mailboxes.

Meanwhile, Darktrace/DMARC helps to reduce the overall attack surface by providing visibility over shadow-IT and third-party vendors sending on behalf of an organization’s brand, while informing recipients when emails from their domains are sent from un-authenticated DMARC source.

Darktrace/DMARC integrates with the wider Darktrace product platform, sharing insights to help further secure your business across Email Attack Path and Attack Surface management.

Conclusion

To learn more about the new innovations to Darktrace/Email download the solution brief here.

All of the new updates to Darktrace/Email sit within the new Darktrace ActiveAI Security Platform, creating a feedback loop between email security and the rest of the digital estate for better protection. Click to read more about the Darktrace ActiveAI Security Platform or to hear about the latest innovations to Darktrace/OT, the most comprehensive prevention, detection, and response solution purpose built for critical infrastructures.

Learn about the intersection of cyber and AI by downloading the State of AI Cyber Security 2024 report to discover global findings that may surprise you, insights from security leaders, and recommendations for addressing today’s top challenges that you may face, too.

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References

[1] Internal Darktrace Research

[2] Internal Darktrace Research

[3] Essential Microsoft Office Statistics in 2024

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About the author

Carlos Gray

Product Manager

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What’s New with Darktrace/Email

Data Loss Prevention

Block the entire spectrum of outbound mail threats with advanced data loss prevention that builds on tags in native email to stop unknown, accidental, and malicious data loss

End User and Security Workflows

Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks1

Microsoft Teams

Detect threats within your Teams environment such as account compromise, phishing, malware and data loss

Lateral Mail Analysis

Detect and respond to internal mailflow with multi-layered AI to prevent account takeover, lateral phishing and data leaks

DMARC

Gain in-depth visibility and control of 3rd parties using your domain with an industry-first AI-assisted DMARC

Conclusion

References

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Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks¹